International market selection decisions - a big data artificial intelligence approach

Abstract

This article examines the role of big data analytics (BDA) in international market selection (IMS) decisions. It is based on a study of South African companies that used the TRADE-DSM (Decision Support Model) big data analytics tool to help in making these decisions. While there is much theory on the potential use of big data analytics and artificial intelligence for international business in general and international market selection decisions in particular, there is very little research on how these tools are used when making this important decision. This article reports on a study that examined: whether big data analytics was used in making international market selection decisions, how important it was relative to other sources of information; how it was used in the international market selection decision-making process; and what factors led to acceptance of big data analytics output. Results from the surveys and interviews both with those who generated the TRADE-DSM reports and the users of the reports (the decision-makers) are presented to provide deeper insights into the role of big data analytics in international market selection decisions. The results showed that while big data analytics is very important (rated third-highest information source), it is one of many sources of information used in the process and that human sources (visits to the market, attendance at trade shows and conferences) are considered the most valuable. Regarding what prompts the acceptance of big data analytics in the international market selection process, the study found that knowledge of the system, trust in the person providing the report and the relationship between the person providing the report and the decision-maker are the most important factors.